forked from phoenix/litellm-mirror
feat(proxy_server.py): dynamic reloading config.yaml with new models
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2 changed files with 42 additions and 63 deletions
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@ -153,6 +153,10 @@ class ProxyChatCompletionRequest(BaseModel):
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class Config:
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extra='allow' # allow params not defined here, these fall in litellm.completion(**kwargs)
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class ModelParams(BaseModel):
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model_name: str
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litellm_params: dict
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user_api_base = None
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user_model = None
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user_debug = False
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@ -162,6 +166,7 @@ user_temperature = None
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user_telemetry = True
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user_config = None
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user_headers = None
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user_config_file_path = None
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local_logging = True # writes logs to a local api_log.json file for debugging
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experimental = False
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#### GLOBAL VARIABLES ####
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@ -315,7 +320,6 @@ def load_from_azure_key_vault(use_azure_key_vault: bool = False):
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except Exception as e:
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print("Error when loading keys from Azure Key Vault. Ensure you run `pip install azure-identity azure-keyvault-secrets`")
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def cost_tracking():
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global prisma_client, master_key
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if prisma_client is not None and master_key is not None:
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@ -405,10 +409,11 @@ def run_ollama_serve():
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""")
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def load_router_config(router: Optional[litellm.Router], config_file_path: str):
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global master_key
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global master_key, user_config_file_path
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config = {}
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try:
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if os.path.exists(config_file_path):
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user_config_file_path = config_file_path
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with open(config_file_path, 'r') as file:
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config = yaml.safe_load(file)
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else:
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@ -947,36 +952,46 @@ async def info_key_fn(key: str = fastapi.Query(..., description="Key in the requ
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#### MODEL MANAGEMENT ####
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#### [BETA] - This is a beta endpoint, format might change based on user feedback. - https://github.com/BerriAI/litellm/issues/964
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@router.post("/model/new", description="Allows adding new models to the model list in the config.yaml", tags=["model management"], dependencies=[Depends(user_api_key_auth)])
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async def add_new_model(model_params: ModelParams):
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global llm_router, llm_model_list, general_settings
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try:
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# Load existing config
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with open(user_config_file_path, "r") as config_file:
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config = yaml.safe_load(config_file)
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# Add the new model to the config
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config['model_list'].append({
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'model_name': model_params.model_name,
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'litellm_params': model_params.litellm_params
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})
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# Save the updated config
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with open(user_config_file_path, "w") as config_file:
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yaml.dump(config, config_file, default_flow_style=False)
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# update Router
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llm_router, llm_model_list, general_settings = load_router_config(router=llm_router, config_file_path=config)
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return {"message": "Model added successfully"}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Internal Server Error: {str(e)}")
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#### [BETA] - This is a beta endpoint, format might change based on user feedback. - https://github.com/BerriAI/litellm/issues/933
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@router.get("/model/info", description="Provides more info about each model in /models, including config.yaml descriptions (except api key and api base)", tags=["model management"], dependencies=[Depends(user_api_key_auth)])
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async def model_info(request: Request):
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global llm_model_list, general_settings
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all_models = []
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if llm_model_list is not None:
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for m in llm_model_list:
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model_dict = {}
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model_name = m["model_name"]
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model_params = {}
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for k,v in m["litellm_params"].items():
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if k == "api_key" or k == "api_base": # don't send the api key or api base
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continue
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if k == "model":
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########## remove -ModelID-XXXX from model ##############
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original_model_string = v
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# Find the index of "ModelID" in the string
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index_of_model_id = original_model_string.find("-ModelID")
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# Remove everything after "-ModelID" if it exists
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if index_of_model_id != -1:
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v = original_model_string[:index_of_model_id]
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else:
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v = original_model_string
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model_params[k] = v
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# Load existing config
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with open(user_config_file_path, "r") as config_file:
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config = yaml.safe_load(config_file)
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all_models = config['model_list']
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model_dict["model_name"] = model_name
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model_dict["model_params"] = model_params
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all_models.append(model_dict)
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for model in all_models:
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# don't return the api key
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model["litellm_params"].pop("api_key", None)
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# all_models = list(set([m["model_name"] for m in llm_model_list]))
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print_verbose(f"all_models: {all_models}")
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return dict(
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@ -991,7 +1006,6 @@ async def model_info(request: Request):
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],
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object="list",
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)
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pass
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#### EXPERIMENTAL QUEUING ####
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@router.post("/queue/request", dependencies=[Depends(user_api_key_auth)])
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async def async_queue_request(request: Request):
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